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Harold Doran; Testsuhiro Yamada; Ted Diaz; Emre Gonulates; Vanessa Culver – Journal of Educational Measurement, 2025
Computer adaptive testing (CAT) is an increasingly common mode of test administration offering improved test security, better measurement precision, and the potential for shorter testing experiences. This article presents a new item selection algorithm based on a generalized objective function to support multiple types of testing conditions and…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Algorithms
Sadeghi, Karim; Abolfazli Khonbi, Zainab – Language Testing in Asia, 2017
As perfectly summarised by Ida Lawrence, "Testing is growing by leaps and bounds across the world. There is a realization that a nation's well-being depends crucially on the educational achievement of its population. Valid tests are an essential tool to evaluate a nation's educational standing and to implement efficacious educational reforms.…
Descriptors: Test Items, Item Response Theory, Computer Assisted Testing, Adaptive Testing
Aybek, Eren Can; Demirtasli, R. Nukhet – International Journal of Research in Education and Science, 2017
This article aims to provide a theoretical framework for computerized adaptive tests (CAT) and item response theory models for polytomous items. Besides that, it aims to introduce the simulation and live CAT software to the related researchers. Computerized adaptive test algorithm, assumptions of item response theory models, nominal response…
Descriptors: Computer Assisted Testing, Adaptive Testing, Item Response Theory, Test Items
Albacete, Patricia; Silliman, Scott; Jordan, Pamela – Grantee Submission, 2017
Intelligent tutoring systems (ITS), like human tutors, try to adapt to student's knowledge level so that the instruction is tailored to their needs. One aspect of this adaptation relies on the ability to have an understanding of the student's initial knowledge so as to build on it, avoiding teaching what the student already knows and focusing on…
Descriptors: Intelligent Tutoring Systems, Knowledge Level, Multiple Choice Tests, Computer Assisted Testing
Moothedath, Shana; Chaporkar, Prasanna; Belur, Madhu N. – Perspectives in Education, 2016
In recent years, the computerised adaptive test (CAT) has gained popularity over conventional exams in evaluating student capabilities with desired accuracy. However, the key limitation of CAT is that it requires a large pool of pre-calibrated questions. In the absence of such a pre-calibrated question bank, offline exams with uncalibrated…
Descriptors: Guessing (Tests), Computer Assisted Testing, Adaptive Testing, Maximum Likelihood Statistics
Thissen, David – Journal of Educational and Behavioral Statistics, 2016
David Thissen, a professor in the Department of Psychology and Neuroscience, Quantitative Program at the University of North Carolina, has consulted and served on technical advisory committees for assessment programs that use item response theory (IRT) over the past couple decades. He has come to the conclusion that there are usually two purposes…
Descriptors: Item Response Theory, Test Construction, Testing Problems, Student Evaluation
Veldkamp, Bernard P.; Matteucci, Mariagiulia; de Jong, Martijn G. – Applied Psychological Measurement, 2013
Item response theory parameters have to be estimated, and because of the estimation process, they do have uncertainty in them. In most large-scale testing programs, the parameters are stored in item banks, and automated test assembly algorithms are applied to assemble operational test forms. These algorithms treat item parameters as fixed values,…
Descriptors: Test Construction, Test Items, Item Banks, Automation
Davey, Tim – Council of Chief State School Officers, 2011
Some brand names are used generically to describe an entire class of products that perform the same function. "Kleenex," "Xerox," "Thermos," and "Band-Aid" are good examples. The term "computerized adaptive testing" (CAT) is similar in that it is often applied uniformly across a diverse family of testing methods. Although the various members of…
Descriptors: Adaptive Testing, Computer Assisted Testing, Delivery Systems, Evaluation Methods
Tendeiro, Jorge N.; Meijer, Rob R. – Applied Psychological Measurement, 2012
This article extends the work by Armstrong and Shi on CUmulative SUM (CUSUM) person-fit methodology. The authors present new theoretical considerations concerning the use of CUSUM person-fit statistics based on likelihood ratios for the purpose of detecting cheating and random guessing by individual test takers. According to the Neyman-Pearson…
Descriptors: Cheating, Individual Testing, Adaptive Testing, Statistics
Dumas, Helene M. – International Journal of Rehabilitation Research, 2010
The PEDI-CAT is a new computer adaptive test (CAT) version of the Pediatric Evaluation of Disability Inventory (PEDI). Additional PEDI-CAT items specific to postacute pediatric hospital care were recently developed using expert reviews and cognitive interviewing techniques. Expert reviews established face and construct validity, providing positive…
Descriptors: Hospitals, Adaptive Testing, Content Validity, Construct Validity
Wang, Hsuan-Po; Kuo, Bor-Chen; Tsai, Ya-Hsun; Liao, Chen-Huei – Turkish Online Journal of Educational Technology - TOJET, 2012
In the era of globalization, the trend towards learning Chinese as a foreign language (CFL) has become increasingly popular worldwide. The increasing demand in learning CFL has raised the profile of the Chinese proficiency test (CPT). This study will analyze in depth the inadequacy of current CPT's utilizing the common European framework of…
Descriptors: Achievement Tests, Adaptive Testing, Computer Assisted Testing, Global Approach
Belov, Dmitry I.; Armstrong, Ronald D. – Educational and Psychological Measurement, 2009
The recent literature on computerized adaptive testing (CAT) has developed methods for creating CAT item pools from a large master pool. Each CAT pool is designed as a set of nonoverlapping forms reflecting the skill levels of an assumed population of test takers. This article presents a Monte Carlo method to obtain these CAT pools and discusses…
Descriptors: Computer Assisted Testing, Adaptive Testing, Item Banks, Test Items
Lee, Yi-Hsuan; Ip, Edward H.; Fuh, Cheng-Der – Educational and Psychological Measurement, 2008
Although computerized adaptive tests have enjoyed tremendous growth, solutions for important problems remain unavailable. One problem is the control of item exposure rate. Because adaptive algorithms are designed to select optimal items, they choose items with high discriminating power. Thus, these items are selected more often than others,…
Descriptors: Adaptive Testing, Computer Assisted Testing, Test Items, Test Validity
Wauters, K.; Desmet, P.; Van den Noortgate, W. – Journal of Computer Assisted Learning, 2010
The popularity of intelligent tutoring systems (ITSs) is increasing rapidly. In order to make learning environments more efficient, researchers have been exploring the possibility of an automatic adaptation of the learning environment to the learner or the context. One of the possible adaptation techniques is adaptive item sequencing by matching…
Descriptors: Knowledge Level, Adaptive Testing, Test Items, Item Response Theory
Chatzopoulou, D. I.; Economides, A. A. – Journal of Computer Assisted Learning, 2010
This paper presents Programming Adaptive Testing (PAT), a Web-based adaptive testing system for assessing students' programming knowledge. PAT was used in two high school programming classes by 73 students. The question bank of PAT is composed of 443 questions. A question is classified in one out of three difficulty levels. In PAT, the levels of…
Descriptors: Student Evaluation, Prior Learning, Programming, High School Students